cs.AI - 人工智能

    cs.CL - 计算与语言 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Conditional LSTM-GAN for Melody Generation from Lyrics
    • [cs.AI]Evaluating Empathy in Artificial Agents
    • [cs.AI]Playing a Strategy Game with Knowledge-Based Reinforcement Learning
    • [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
    • [cs.AI]Tracing Player Knowledge in a Parallel Programming Educational Game
    • [cs.CL]A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
    • [cs.CL]A Multivariate Model for Representing Semantic Non-compositionality
    • [cs.CL]Feature-Less End-to-End Nested Term Extraction
    • [cs.CL]Multi-Task Self-Supervised Learning for Disfluency Detection
    • [cs.CL]Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
    • [cs.CL]Raw-to-End Name Entity Recognition in Social Media
    • [cs.CL]SenseBERT: Driving Some Sense into BERT
    • [cs.CL]Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability
    • [cs.CL]Towards Knowledge-Based Recommender Dialog System
    • [cs.CL]Visualizing and Understanding the Effectiveness of BERT
    • [cs.CL]What’s Wrong with Hebrew NLP? And How to Make it Right
    • [cs.CL]X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
    • [cs.CL]XCMRC: Evaluating Cross-lingual Machine Reading Comprehension
    • [cs.CV]3D Human Pose Estimation under limited supervision using Metric Learning
    • [cs.CV]A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
    • [cs.CV]Accelerated CNN Training Through Gradient Approximation
    • [cs.CV]Beyond Cartesian Representations for Local Descriptors
    • [cs.CV]Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
    • [cs.CV]Deep learning for Plankton and Coral Classification
    • [cs.CV]Dual Adversarial Inference for Text-to-Image Synthesis
    • [cs.CV]FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
    • [cs.CV]Improved Mix-up with KL-Entropy for Learning From Noisy Labels
    • [cs.CV]IoU-balanced Loss Functions for Single-stage Object Detection
    • [cs.CV]Learning Trajectory Dependencies for Human Motion Prediction
    • [cs.CV]PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation
    • [cs.CV]R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
    • [cs.CV]SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks
    • [cs.CV]To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation
    • [cs.CV]Unpaired Cross-lingual Image Caption Generation with Self-Supervised Rewards
    • [cs.CY]A blockchain-based user-centric emission monitoring and trading system for multi-modal mobility
    • [cs.CY]Producers of Popular Science Web Videos. Between New Professionalism and Old Gender Issues
    • [cs.DC]Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine Attacks
    • [cs.IR]CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation
    • [cs.IR]FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach
    • [cs.IR]Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
    • [cs.IR]GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
    • [cs.IR]Hamming Sentence Embeddings for Information Retrieval
    • [cs.IR]SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
    • [cs.IR]Two-stage Federated Phenotyping and Patient Representation Learning
    • [cs.IT]Diffusive Mobile MC with Absorbing Receivers: Stochastic Analysis and Applications
    • [cs.IT]Ergodic Rate Analysis of Cooperative Ambient Backscatter Communication
    • [cs.IT]Generalized Haar condition-based phaseless random sampling for compactly supported functions in shift-invariant spaces
    • [cs.IT]Non-coherent Detection and Bit Error Rate for an Ambient Backscatter Link in Time-Selective Fading
    • [cs.LG]Adaptive Regularization of Labels
    • [cs.LG]Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss
    • [cs.LG]Domain-adversarial Network Alignment
    • [cs.LG]From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning — Insights from Biological Systems on Adaptive Flexibility
    • [cs.LG]HONEM: Network Embedding Using Higher-Order Patterns in Sequential Data
    • [cs.LG]Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters
    • [cs.LG]Learning Credible Deep Neural Networks with Rationale Regularization
    • [cs.LG]Mapping State Space using Landmarks for Universal Goal Reaching
    • [cs.LG]PHYRE: A New Benchmark for Physical Reasoning
    • [cs.LG]Predicting Eating Events in Free Living Individuals — A Technical Report
    • [cs.LG]Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems
    • [cs.LG]Sex Trafficking Detection with Ordinal Regression Neural Networks
    • [cs.LG]Temporal Collaborative Ranking Via Personalized Transformer
    • [cs.LG]Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools
    • [cs.LO]Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems
    • [cs.LO]Vector spaces as Kripke frames
    • [cs.MA]Massive Multi-Agent Data-Driven Simulations of the GitHub Ecosystem
    • [cs.NE]MOEA/D with Uniformly Randomly Adaptive Weights
    • [cs.NI]Distributed Rate Control in Downlink NOMA Networks with Reliability Constraints
    • [cs.PL]CLOTHO: Directed Test Generation for Weakly Consistent Database Systems
    • [cs.RO]Comparing Metrics for Robustness Against External Perturbations in Dynamic Trajectory Optimization
    • [cs.RO]Distributed Path Planning for Executing Cooperative Tasks with Time Windows
    • [cs.RO]Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
    • [cs.RO]Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction
    • [cs.SI]On Gossip-based Information Dissemination in Pervasive Recommender Systems
    • [cs.SI]When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian
    • [eess.IV]A Multimodal Vision Sensor for Autonomous Driving
    • [eess.IV]A deep learning model for segmentation of geographic atrophy to study its long-term natural history
    • [eess.IV]Automated Rib Fracture Detection of Postmortem Computed Tomography Images Using Machine Learning Techniques
    • [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
    • [eess.IV]Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
    • [eess.IV]Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography
    • [eess.IV]Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery
    • [eess.IV]Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
    • [eess.IV]Towards multi-sequence MR image recovery from undersampled k-space data
    • [eess.SP]On the Age of Information of Short-Packet Communications with Packet Management
    • [math.OC]Distributionally Robust Optimization: A Review
    • [math.ST]Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso
    • [math.ST]Exponential two-armed bandit problem
    • [math.ST]Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis
    • [math.ST]The generalization error of random features regression: Precise asymptotics and double descent curve
    • [physics.comp-ph]Cosmological N-body simulations: a challenge for scalable generative models
    • [physics.soc-ph]Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
    • [q-bio.PE]Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model
    • [q-bio.PE]Epidemic models on social networks — with inference
    • [stat.AP]A hierarchical model for estimating exposure-response curves from multiple studies
    • [stat.AP]Learning Signal Subgraphs from Longitudinal Brain Networks with Symmetric Bilinear Logistic Regression
    • [stat.AP]Robust parametric modeling of Alzheimer’s disease progression
    • [stat.ME]A grouped, selectively weighted false discovery rate procedure
    • [stat.ME]A hypothesis test of feasibility for external pilot trials assessing recruitment, follow-up and adherence rates
    • [stat.ME]False Discovery Rate for Functional Data
    • [stat.ME]With Malice Towards None: Assessing Uncertainty via Equalized Coverage
    • [stat.ML]A Bayesian Choice Model for Eliminating Feedback Loops
    • [stat.ML]Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
    • [stat.ML]End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks
    • [stat.ML]Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
    • [stat.ML]Mixed pooling of seasonality in time series pallet forecasting
    • [stat.ML]Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems
    • [stat.ML]Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile
    • [stat.ML]Uplift Modeling for Multiple Treatments with Cost Optimization

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    • [cs.AI]Conditional LSTM-GAN for Melody Generation from Lyrics
    Yi Yu, Simon Canales
    http://arxiv.org/abs/1908.05551v1

    • [cs.AI]Evaluating Empathy in Artificial Agents
    Özge Nilay Yalçın
    http://arxiv.org/abs/1908.05341v1

    • [cs.AI]Playing a Strategy Game with Knowledge-Based Reinforcement Learning
    Viktor Voss, Liudmyla Nechepurenko, Dr. Rudi Schaefer, Steffen Bauer
    http://arxiv.org/abs/1908.05472v1

    • [cs.AI]Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
    Tom Everitt, Marcus Hutter
    http://arxiv.org/abs/1908.04734v2

    • [cs.AI]Tracing Player Knowledge in a Parallel Programming Educational Game
    Pavan Kantharaju, Katelyn Alderfer, Jichen Zhu, Bruce Char, Brian Smith, Santiago Ontañón
    http://arxiv.org/abs/1908.05632v1

    • [cs.CL]A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning
    Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
    http://arxiv.org/abs/1908.05514v1

    • [cs.CL]A Multivariate Model for Representing Semantic Non-compositionality
    Meghdad Farahmand
    http://arxiv.org/abs/1908.05490v1

    • [cs.CL]Feature-Less End-to-End Nested Term Extraction
    Yuze Gao, Yu Yuan
    http://arxiv.org/abs/1908.05426v1

    • [cs.CL]Multi-Task Self-Supervised Learning for Disfluency Detection
    Shaolei Wang, Wanxiang Che, Qi Liu, Pengda Qin, Ting Liu, William Yang Wang
    http://arxiv.org/abs/1908.05378v1

    • [cs.CL]Multi-class Hierarchical Question Classification for Multiple Choice Science Exams
    Dongfang Xu, Peter Jansen, Jaycie Martin, Zhengnan Xie, Vikas Yadav, Harish Tayyar Madabushi, Oyvind Tafjord, Peter Clark
    http://arxiv.org/abs/1908.05441v1

    • [cs.CL]Raw-to-End Name Entity Recognition in Social Media
    Liyuan Liu, Zihan Wang, Jingbo Shang, Dandong Yin, Heng Ji, Xiang Ren, Shaowen Wang, Jiawei Han
    http://arxiv.org/abs/1908.05344v1

    • [cs.CL]SenseBERT: Driving Some Sense into BERT
    Yoav Levine, Barak Lenz, Or Dagan, Dan Padnos, Or Sharir, Shai Shalev-Shwartz, Amnon Shashua, Yoav Shoham
    http://arxiv.org/abs/1908.05646v1

    • [cs.CL]Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability
    Zhuoxuan Jiang, Xian-Ling Mao, Ziming Huang, Jie Ma, Shaochun Li
    http://arxiv.org/abs/1908.05408v1

    • [cs.CL]Towards Knowledge-Based Recommender Dialog System
    Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang
    http://arxiv.org/abs/1908.05391v1

    • [cs.CL]Visualizing and Understanding the Effectiveness of BERT
    Yaru Hao, Li Dong, Furu Wei, Ke Xu
    http://arxiv.org/abs/1908.05620v1

    • [cs.CL]What’s Wrong with Hebrew NLP? And How to Make it Right
    Reut Tsarfaty, Amit Seker, Shoval Sadde, Stav Klein
    http://arxiv.org/abs/1908.05453v1

    • [cs.CL]X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
    Mostafa Abdou, Cezar Sas, Rahul Aralikatte, Isabelle Augenstein, Anders Søgaard
    http://arxiv.org/abs/1908.05111v2

    • [cs.CL]XCMRC: Evaluating Cross-lingual Machine Reading Comprehension
    Pengyuan Liu, Yuning Deng, Chenghao Zhu, Han Hu
    http://arxiv.org/abs/1908.05416v1

    • [cs.CV]3D Human Pose Estimation under limited supervision using Metric Learning
    Rahul Mitra, Nitesh B. Gundavarapu, Sudharshan Chandra Babu, Prashasht Bindal, Abhishek Sharma, Arjun Jain
    http://arxiv.org/abs/1908.05293v1

    • [cs.CV]A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning
    Pengfei Wang, Chengquan Zhang, Fei Qi, Zuming Huang, Mengyi En, Junyu Han, Jingtuo Liu, Errui Ding, Guangming Shi
    http://arxiv.org/abs/1908.05498v1

    • [cs.CV]Accelerated CNN Training Through Gradient Approximation
    Ziheng Wang, Sree Harsha Nelaturu
    http://arxiv.org/abs/1908.05460v1

    • [cs.CV]Beyond Cartesian Representations for Local Descriptors
    Patrick Ebel, Anastasiia Mishchuk, Kwang Moo Yi, Pascal Fua, Eduard Trulls
    http://arxiv.org/abs/1908.05547v1

    • [cs.CV]Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
    Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana, Keerthi Ram, Jayaraj Joseph, Mohanasankar Sivaprakasam
    http://arxiv.org/abs/1908.05311v1

    • [cs.CV]Deep learning for Plankton and Coral Classification
    Alessandra Lumini, Loris Nanni, Gianluca Maguolo
    http://arxiv.org/abs/1908.05489v1

    • [cs.CV]Dual Adversarial Inference for Text-to-Image Synthesis
    Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader, Francis Dutil, Lisa Di Jorio, Thomas Fevens
    http://arxiv.org/abs/1908.05324v1

    • [cs.CV]FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
    Jiabin Zhang, Zheng Zhu, Wei Zou, Peng Li, Yanwei Li, Hu Su, Guan Huang
    http://arxiv.org/abs/1908.05593v1

    • [cs.CV]Improved Mix-up with KL-Entropy for Learning From Noisy Labels
    Qian Zhang, Feifei Lee, Ya-Gang Wang, Qiu Chen
    http://arxiv.org/abs/1908.05488v1

    • [cs.CV]IoU-balanced Loss Functions for Single-stage Object Detection
    Shengkai Wu, Xiaoping Li
    http://arxiv.org/abs/1908.05641v1

    • [cs.CV]Learning Trajectory Dependencies for Human Motion Prediction
    Wei Mao, Miaomiao Liu, Mathieu Salzmann, Hongdong Li
    http://arxiv.org/abs/1908.05436v1

    • [cs.CV]PS^2-Net: A Locally and Globally Aware Network for Point-Based Semantic Segmentation
    Na Zhao, Tat-Seng Chua, Gim Hee Lee
    http://arxiv.org/abs/1908.05425v1

    • [cs.CV]R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
    Xue Yang, Qingqing Liu, Junchi Yan, Ang Li
    http://arxiv.org/abs/1908.05612v1

    • [cs.CV]SFSegNet: Parse Freehand Sketches using Deep Fully Convolutional Networks
    Junkun Jiang, Ruomei Wang, Shujin Lin, Fei Wang
    http://arxiv.org/abs/1908.05389v1

    • [cs.CV]To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation
    Amir Atapour-Abarghouei, Toby P. Breckon
    http://arxiv.org/abs/1908.05540v1

    • [cs.CV]Unpaired Cross-lingual Image Caption Generation with Self-Supervised Rewards
    Yuqing Song, Shizhe Chen, Yida Zhao, Qin Jin
    http://arxiv.org/abs/1908.05407v1

    • [cs.CY]A blockchain-based user-centric emission monitoring and trading system for multi-modal mobility
    Johannes Eckert, David López, Carlos Lima Azevedo, Bilal Farooq
    http://arxiv.org/abs/1908.05629v1

    • [cs.CY]Producers of Popular Science Web Videos. Between New Professionalism and Old Gender Issues
    Jesus Munoz Morcillo, Klemens Czurda, Andrea Geipel, Caroline Y. Robertson-von Trotha
    http://arxiv.org/abs/1908.05572v1

    • [cs.DC]Secure Coded Cooperative Computation at the Heterogeneous Edge against Byzantine Attacks
    Yasaman Keshtkarjahromi, Rawad Bitar, Venkat Dasari, Salim El Rouayheb, Hulya Seferoglu
    http://arxiv.org/abs/1908.05385v1

    • [cs.IR]CUPCF: Combining Users Preferences in Collaborative Filtering for Better Recommendation
    Mostafa Khalaji, Nilufar Mohammadnejad
    http://arxiv.org/abs/1908.05609v1

    • [cs.IR]FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach
    Mostafa Khalaji, Nilufar Mohammadnejad
    http://arxiv.org/abs/1908.05608v1

    • [cs.IR]Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA System
    Ye Liu, Chenwei Zhang, Xiaohui Yan, Yi Chang, Philip S. Yu
    http://arxiv.org/abs/1908.05604v1

    • [cs.IR]GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model
    Chang-You Tai, Meng-Ru Wu, Yun-Wei Chu, Shao-Yu Chu
    http://arxiv.org/abs/1908.05611v1

    • [cs.IR]Hamming Sentence Embeddings for Information Retrieval
    Felix Hamann, Nadja Kurz, Adrian Ulges
    http://arxiv.org/abs/1908.05541v1

    • [cs.IR]SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep Hashing
    Heikki Arponen, Tom E Bishop
    http://arxiv.org/abs/1908.05602v1

    • [cs.IR]Two-stage Federated Phenotyping and Patient Representation Learning
    Dianbo Liu, Dmitriy Dligach, Timothy Miller
    http://arxiv.org/abs/1908.05596v1

    • [cs.IT]Diffusive Mobile MC with Absorbing Receivers: Stochastic Analysis and Applications
    Trang Ngoc Cao, Arman Ahmadzadeh, Vahid Jamali, Wayan Wicke, Phee Lep Yeoh, Jamie Evans, Robert Schober
    http://arxiv.org/abs/1908.05600v1

    • [cs.IT]Ergodic Rate Analysis of Cooperative Ambient Backscatter Communication
    Shaoqing Zhou, Wei Xu, Kezhi Wang, Cunhua Pan, Mohamed-Slim Alouini, Arumugam Nallanathan
    http://arxiv.org/abs/1908.05455v1

    • [cs.IT]Generalized Haar condition-based phaseless random sampling for compactly supported functions in shift-invariant spaces
    Youfa Li, Wenchang Sun
    http://arxiv.org/abs/1908.05423v1

    • [cs.IT]Non-coherent Detection and Bit Error Rate for an Ambient Backscatter Link in Time-Selective Fading
    J. Kartheek Devineni, Harpreet S. Dhillon
    http://arxiv.org/abs/1908.05657v1

    • [cs.LG]Adaptive Regularization of Labels
    Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Shu-Tao Xia
    http://arxiv.org/abs/1908.05474v1

    • [cs.LG]Distinction Maximization Loss: Fast, Scalable, Turnkey, and Native Neural Networks Out-of-Distribution Detection simply by Replacing the SoftMax Loss
    David Macêdo
    http://arxiv.org/abs/1908.05569v1

    • [cs.LG]Domain-adversarial Network Alignment
    Huiting Hong, Xin Li, Yuangang Pan, Ivor Tsang
    http://arxiv.org/abs/1908.05429v1

    • [cs.LG]From Crystallized Adaptivity to Fluid Adaptivity in Deep Reinforcement Learning — Insights from Biological Systems on Adaptive Flexibility
    Malte Schilling, Helge Ritter, Frank W. Ohl
    http://arxiv.org/abs/1908.05348v1

    • [cs.LG]HONEM: Network Embedding Using Higher-Order Patterns in Sequential Data
    Mandana Saebi, Giovanni Luca Ciampaglia, Lance M Kaplan, Nitesh V Chawla
    http://arxiv.org/abs/1908.05387v1

    • [cs.LG]Improving Randomized Learning of Feedforward Neural Networks by Appropriate Generation of Random Parameters
    Grzegorz Dudek
    http://arxiv.org/abs/1908.05542v1

    • [cs.LG]Learning Credible Deep Neural Networks with Rationale Regularization
    Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu
    http://arxiv.org/abs/1908.05601v1

    • [cs.LG]Mapping State Space using Landmarks for Universal Goal Reaching
    Zhiao Huang, Fangchen Liu, Hao Su
    http://arxiv.org/abs/1908.05451v1

    • [cs.LG]PHYRE: A New Benchmark for Physical Reasoning
    Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross Girshick
    http://arxiv.org/abs/1908.05656v1

    • [cs.LG]Predicting Eating Events in Free Living Individuals — A Technical Report
    Jiayi Wang, Jiue-An Yang, Supun Nakandala, Arun Kumar, Marta M. Jankowska
    http://arxiv.org/abs/1908.05304v1

    • [cs.LG]Resonant Machine Learning Based on Complex Growth Transform Dynamical Systems
    Oindrila Chatterjee, Shantanu Chakrabartty
    http://arxiv.org/abs/1908.05377v1

    • [cs.LG]Sex Trafficking Detection with Ordinal Regression Neural Networks
    Longshaokan Wang, Eric Laber, Yeng Saanchi, Sherrie Caltagirone
    http://arxiv.org/abs/1908.05434v1

    • [cs.LG]Temporal Collaborative Ranking Via Personalized Transformer
    Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
    http://arxiv.org/abs/1908.05435v1

    • [cs.LG]Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools
    Anh Truong, Austin Walters, Jeremy Goodsitt, Keegan Hines, Bayan Bruss, Reza Farivar
    http://arxiv.org/abs/1908.05557v1

    • [cs.LO]Shield Synthesis for Real: Enforcing Safety in Cyber-Physical Systems
    Meng Wu, Jingbo Wang, Jyotirmoy Deshmukh, Chao Wang
    http://arxiv.org/abs/1908.05402v1

    • [cs.LO]Vector spaces as Kripke frames
    Giuseppe Greco, Fei Liang, Michael Moortgat, Alessandra Palmigiano
    http://arxiv.org/abs/1908.05528v1

    • [cs.MA]Massive Multi-Agent Data-Driven Simulations of the GitHub Ecosystem
    Jim Blythe, John Bollenbacher, Di Huang, Pik-Mai Hui, Rachel Krohn, Diogo Pacheco, Goran Muric, Anna Sapienza, Alexey Tregubov, Yong-Yeol Ahn, Alessandro Flammini, Kristina Lerman, Filippo Menczer, Tim Weninger, Emilio Ferrara
    http://arxiv.org/abs/1908.05437v1

    • [cs.NE]MOEA/D with Uniformly Randomly Adaptive Weights
    Lucas R. C. de Farias, Pedro H. M. Braga, Hansenclever F. Bassani, Aluizio F. R. Araújo
    http://arxiv.org/abs/1908.05383v1

    • [cs.NI]Distributed Rate Control in Downlink NOMA Networks with Reliability Constraints
    Onel L. A. López, Hirley Alves, Matti Latva-aho
    http://arxiv.org/abs/1908.05513v1

    • [cs.PL]CLOTHO: Directed Test Generation for Weakly Consistent Database Systems
    Kia Rahmani, Kartik Nagar, Benjamin Delaware, Suresh Jagannathan
    http://arxiv.org/abs/1908.05655v1

    • [cs.RO]Comparing Metrics for Robustness Against External Perturbations in Dynamic Trajectory Optimization
    Henrique Ferrolho, Wolfgang Merkt, Carlo Tiseo, Sethu Vijayakumar
    http://arxiv.org/abs/1908.05380v1

    • [cs.RO]Distributed Path Planning for Executing Cooperative Tasks with Time Windows
    Raghavendra Bhat, Yasin Yazicioglu, Derya Aksaray
    http://arxiv.org/abs/1908.05630v1

    • [cs.RO]Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
    Joseph Campbell, Arne Hitzmann, Simon Stepputtis, Shuhei Ikemoto, Koh Hosoda, Heni Ben Amor
    http://arxiv.org/abs/1908.05552v1

    • [cs.RO]Sample-efficient Deep Reinforcement Learning with Imaginary Rollouts for Human-Robot Interaction
    Mohammad Thabet, Massimiliano Patacchiola, Angelo Cangelosi
    http://arxiv.org/abs/1908.05546v1

    • [cs.SI]On Gossip-based Information Dissemination in Pervasive Recommender Systems
    Tobias Eichinger, Felix Beierle, Robin Papke, Lucas Rebscher, Hong Chinh Tran, Magdalena Trzeciak
    http://arxiv.org/abs/1908.05544v1

    • [cs.SI]When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian
    Hancheng Cao, Zhilong Chen, Fengli Xu, Tao Wang, Yujian Xu, Lianglun Zhang, Yong Li
    http://arxiv.org/abs/1908.05409v1

    • [eess.IV]A Multimodal Vision Sensor for Autonomous Driving
    Dongming Sun, Xiao Huang, Kailun Yang
    http://arxiv.org/abs/1908.05649v1

    • [eess.IV]A deep learning model for segmentation of geographic atrophy to study its long-term natural history
    Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo, Timo Verzijden, Paul Mitchell, Carel B. Hoyng, Bram van Ginneken, Caroline C. W. Klaver, Clara I. Sánchez
    http://arxiv.org/abs/1908.05621v1

    • [eess.IV]Automated Rib Fracture Detection of Postmortem Computed Tomography Images Using Machine Learning Techniques
    Samuel Gunz, Svenja Erne, Eric J. Rawdon, Garyfalia Ampanozi, Till Sieberth, Raffael Affolter, Lars C. Ebert, Akos Dobay
    http://arxiv.org/abs/1908.05467v1

    • [eess.IV]Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
    Anna Kuzina, Evgenii Egorov, Evgeny Burnaev
    http://arxiv.org/abs/1908.05480v1

    • [eess.IV]Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement
    Cheng Peng, Wei-An Lin, Haofu Liao, Rama Chellappa, S. Kevin Zhou
    http://arxiv.org/abs/1908.05599v1

    • [eess.IV]Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography
    Jelmer M. Wolterink, Tim Leiner, Ivana Išgum
    http://arxiv.org/abs/1908.05343v1

    • [eess.IV]Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery
    Szu-Yeu Hu, Wei-Hung Weng, Shao-Lun Lu, Yueh-Hung Cheng, Furen Xiao, Feng-Ming Hsu, Jen-Tang Lu
    http://arxiv.org/abs/1908.05418v1

    • [eess.IV]Recognition of Ischaemia and Infection in Diabetic Foot Ulcers: Dataset and Techniques
    Manu Goyal, Neil Reeves, Satyan Rajbhandari, Naseer Ahmad, Chuan Wang, Moi Hoon Yap
    http://arxiv.org/abs/1908.05317v1

    • [eess.IV]Towards multi-sequence MR image recovery from undersampled k-space data
    Cheng Peng, Wei-An Lin, Rama Chellappa, S. Kevin Zhou
    http://arxiv.org/abs/1908.05615v1

    • [eess.SP]On the Age of Information of Short-Packet Communications with Packet Management
    Rui Wang, Yifan Gu, He Chen, Yonghui Li, Branka Vucetic
    http://arxiv.org/abs/1908.05447v1

    • [math.OC]Distributionally Robust Optimization: A Review
    Hamed Rahimian, Sanjay Mehrotra
    http://arxiv.org/abs/1908.05659v1

    • [math.ST]Efficient Estimation of Pathwise Differentiable Target Parameters with the Undersmoothed Highly Adaptive Lasso
    Mark J. van der Laan, David Benkeser, Weixin Cai
    http://arxiv.org/abs/1908.05607v1

    • [math.ST]Exponential two-armed bandit problem
    Alexander Kolnogorov, Denis Grunev
    http://arxiv.org/abs/1908.05531v1

    • [math.ST]Robust One-Bit Recovery via ReLU Generative Networks: Improved Statistical Rates and Global Landscape Analysis
    Shuang Qiu, Xiaohan Wei, Zhuoran Yang
    http://arxiv.org/abs/1908.05368v1

    • [math.ST]The generalization error of random features regression: Precise asymptotics and double descent curve
    Song Mei, Andrea Montanari
    http://arxiv.org/abs/1908.05355v1

    • [physics.comp-ph]Cosmological N-body simulations: a challenge for scalable generative models
    Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Réfrégier
    http://arxiv.org/abs/1908.05519v1

    • [physics.soc-ph]Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
    Felix M. Strnad, Wolfram Barfuss, Jonathan F. Donges, Jobst Heitzig
    http://arxiv.org/abs/1908.05567v1

    • [q-bio.PE]Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model
    Jennifer F. Hoyal Cuthill, Nicholas Guttenberg, Sophie Ledger, Robyn Crowther, Blanca Huertas
    http://arxiv.org/abs/1908.05635v1

    • [q-bio.PE]Epidemic models on social networks — with inference
    Tom Britton
    http://arxiv.org/abs/1908.05517v1

    • [stat.AP]A hierarchical model for estimating exposure-response curves from multiple studies
    Joshua P. Keller, Joanne Katz, Amid K. Pokhrel, Michael N. Bates, James Tielsch, Scott L. Zeger
    http://arxiv.org/abs/1908.05340v1

    • [stat.AP]Learning Signal Subgraphs from Longitudinal Brain Networks with Symmetric Bilinear Logistic Regression
    Lu Wang, Zhengwu Zhang
    http://arxiv.org/abs/1908.05627v1

    • [stat.AP]Robust parametric modeling of Alzheimer’s disease progression
    Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, Marc Modat, M. Jorge Cardoso, Sébastien Ourselin, Lauge Sørensen
    http://arxiv.org/abs/1908.05338v1

    • [stat.ME]A grouped, selectively weighted false discovery rate procedure
    Xiongzhi Chen, Sanat K. Sarkar
    http://arxiv.org/abs/1908.05319v1

    • [stat.ME]A hypothesis test of feasibility for external pilot trials assessing recruitment, follow-up and adherence rates
    Duncan T. Wilson, Rebecca E. A. Walwyn, Julia Brown, Amanda J. Farrin
    http://arxiv.org/abs/1908.05562v1

    • [stat.ME]False Discovery Rate for Functional Data
    Niels Lundtorp Olsen, Alessia Pini, Simone Vantini
    http://arxiv.org/abs/1908.05272v1

    • [stat.ME]With Malice Towards None: Assessing Uncertainty via Equalized Coverage
    Yaniv Romano, Rina Foygel Barber, Chiara Sabatti, Emmanuel J. Candès
    http://arxiv.org/abs/1908.05428v1

    • [stat.ML]A Bayesian Choice Model for Eliminating Feedback Loops
    Gökhan Çapan, İlker Gündoğdu, Ali Caner Türkmen, Çağrı\ Sofuoğlu, Ali Taylan Cemgil
    http://arxiv.org/abs/1908.05640v1

    • [stat.ML]Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
    Ola Spjuth, Robin Carrión Brännström, Lars Carlsson, Niharika Gauraha
    http://arxiv.org/abs/1908.05571v1

    • [stat.ML]End-to-End Learning from Complex Multigraphs with Latent Graph Convolutional Networks
    Floris Hermsen, Peter Bloem, Fabian Jansen, Wolf Vos
    http://arxiv.org/abs/1908.05365v1

    • [stat.ML]Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
    Zhenyu Zhao, Radhika Anand, Mallory Wang
    http://arxiv.org/abs/1908.05376v1

    • [stat.ML]Mixed pooling of seasonality in time series pallet forecasting
    Hyunji Moon, Hyeonseop Lee
    http://arxiv.org/abs/1908.05339v1

    • [stat.ML]Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems
    Mohsen Shahhosseini, Guiping Hu, Hieu Pham
    http://arxiv.org/abs/1908.05287v1

    • [stat.ML]Sequential Computer Experimental Design for Estimating an Extreme Probability or Quantile
    Hao Chen, William J. Welch
    http://arxiv.org/abs/1908.05357v1

    • [stat.ML]Uplift Modeling for Multiple Treatments with Cost Optimization
    Zhenyu Zhao, Totte Harinen
    http://arxiv.org/abs/1908.05372v1